Parkinson Gait Quantification Classification Assessment Based On Digital Field

Parkinson’s Disease is an common neurological disease, gait disorder as a typical clinical symptoms of the disease, often leads to a unstable walk even fall, it have a serious impact on the life quality of the PD patients. At present, the diagnosis and assessment of gait disorder for the PD patients mainly depends on the physician’s clinical experience, because of its strong subjectivity, there often appear big difference for the judgment of the same patients between different physicians. Therefore, develop the quantitative measurement and evaluation technology of the clinical gait disorder for the PD patients, can strengthen the objectivity and accuracy of the diagnosis and treatment effect, reduce the cost of social medical treatment and patients life care, and improve the life quality of the patients.At present, the quantitative measurement and evaluation of the gait disorder for the PD patients is mainly use the gait analysis system consist by the3-D images, inertial unit, pedal switch, force sensor, or handled camera equipment, but the gait analysis system based on 3-D images is often expensive and operate complex; The inertial unit and handled camera although convenient to operate and wearing, but the measurement results are inaccurate; The pedal switch also have big deviation; The electronic trail based on the force sensor can only get a short straight information, can not capture the gait characteristic around the corner. Aiming at the shortcoming above, we designed and complemented a Parkinson gait disorder graded evaluation system and method by using the digital field, which is mainly include the Parkinson gait analysis system and gait quantitative classification method. The main work of this paper is as follows:1. Summarizing and analyzing the research background, research significance and development survey at home and abroad, discussing the theory, application and disadvantages of the existing gait analysis system and gait evaluation method.2. Introducing the overall design and implementation of the Parkinson gait analysis system in detail. Through the analysis of the functional and performance requirements to the system, we confirming the design task and the index, and then we designing and building the software and hardware platform of the system and completing every function module, mainly include the flexible sensor unit module, data acquisition, transmission circuit of the hardware system and the data collection, data analysis, personnel information management module of the software system.3. Elaborating the gait feature parameter extraction method and procedure detailed. Introducing the data preprocessing, mainly include the data denoising, data clustering, footprint type identification, after that, expounding the gait feature type and extraction method according to the characteristics of the gait cycle in the normal walking process, which is include the kinematic parameters, kinetic parameters, and the gait feature of our only.4. Proposing a Parkinson gait quantitative classification method based on the fuzzy logic. By analysis the gait feature above, a gait feature subset of higher correlation with the classification is filtered, and then we set up the fuzzy rules and select the suitable fuzzy membership function, and establish the fuzzy classifier, which can be used to achieve the gait quantitative classification of the PD patients.5. Discussing and analyzing the experimental results.136 PD patients are selected as the test sample, we extracting their gait features, and divide them into three categories by using the fuzzy classifier, then calculating the classification accuracy and sensitivity according to the clinical physicians’ score, to validate the reliability of our method.The experiment results showing that the classification accuracy and sensitivity of the method is 91%, can effectively achieve the clinical gait quantitative grade evaluation of the gait disorder for PD patients, which can further demonstrate the effectiveness of our proposing gait quantitative grading evaluation scheme based on the digital field.